Zobrazeno 1 - 10 of 180 pro vyhledávání: '"Kohei Shiomoto"'
3
Network Intrusion Detection System Based on an Adversarial Auto-Encoder with Few Labeled Training Samples
Autor: Kohei Shiomoto
Publikováno v: Journal of Network and Systems Management. 31
Network intrusion detection systems (NIDS) are critical to defending network systems from cyber attacks. Recently, machine learning has been applied to enhance NIDS capability. To train a supervised machine-learning model, a large number of labeled t
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::fdff31b8bc77fde9a0226bc62985895e
https://doi.org/10.1007/s10922-022-09698-w
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4
Few-Shot Learning and Self-Training for eNodeB Log Analysis for Service-Level Assurance in LTE Networks
Autor: Shogo Aoki, Chin Lam Eng, Kohei Shiomoto
Publikováno v: IEEE Transactions on Network and Service Management. 17:2077-2089
With the increasing network topology complexity and continuous evolution of the new wireless technology, it is challenging to address the network service outage with traditional methods. In the long-term evolution (LTE) networks, a large number of ba
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::c8b15f372fe95665171a3230ad8da444
https://doi.org/10.1109/tnsm.2020.3032156
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6
A Network and Computing Resource Management Method based on Population Prediction in Mobile Networks
Autor: Kohei Shiomoto, Tatsuya Otoshi, Masayuki Murata
Publikováno v: NoF
Existing traffic prediction methods are based on previously collected traffic patterns. The measured data is used to train and create a model, and the model predicts future traffic patterns. However, mobile traffic accounts for the majority of networ
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::d803113bbeeb2e10ff3ee6c0053cb2ed
https://doi.org/10.1109/nof52522.2021.9609894
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7
Policy Gradient-based Deep Reinforcement Learning for Deadline-aware Transfer over Wide Area Networks
Autor: Kohei Shiomoto, Takashi Kurimoto
Publikováno v: NetSoft
Deadline-aware job scheduling problems have been attracting attention in the application domains of scientific workflows and commercial data-center wide area networks. Satisfying all of the demands before the corresponding deadlines requires optimall
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::eb417d6e66be5199fe5da6b5fc9aa90b
https://doi.org/10.1109/netsoft51509.2021.9492675
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9
End-to-End Management of All Optical Disaggregated Network and Applications with Cloud Native Environment for the Smart World Network Infrastructure
Autor: Takahiro Hirayama, Satoru Okamoto, Masaki Murakami, Kohei Shiomoto, Noboru Yoshikane, Hyde Sugiyama, Shinya Nakamura, Satoshi Yamanoi, Yusuke Hirota
Publikováno v: 26th Optoelectronics and Communications Conference.
We show a multi-cloud-based network infrastructure for Smart World with demonstrating several types of network control and service including PTP devices for Private LTE, AI-based SFC Platform, WhiteBox-based reliable routing, and disaggregated SDM ne
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::4bdb789d3a57f07572a99a363d04e345
https://doi.org/10.1364/oecc.2021.m4a.4
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10
Performance change with the number of training data: A case study on the binary classification of COVID-19 chest X-ray by using convolutional neural networks
Autor: Kohei Shiomoto, Kuniki Imagawa
Publikováno v: Computers in Biology and Medicine. 142:105251
One of the features of artificial intelligence/machine learning-based medical devices resides in their ability to learn from real-world data. However, obtaining a large number of training data in the early phase is difficult, and the device performan
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a972e8cf4817ed415a158cb4a0af9950
https://doi.org/10.1016/j.compbiomed.2022.105251
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